Risk-O-Meter: An Intelligent Clinical Risk Calculator

We present a system called Risk-O-Meter to predict and analyze clinical risk via data imputation, visualization, predictive modeling, and association rule exploration. Clinical risk calculators provide information about a person's chance of having a disease or encountering a clinical event. Such tools could be highly useful to educate patients to understand and monitor their health conditions. Unlike existing risk calculators that are primarily designed for domain experts, Risk-O-Meter is useful to patients who are unfamiliar with medical terminologies, or providers who have limited information about a patient. Risk-O-Meter is designed in a way such that it is exible enough to accept limited or incomplete data inputs, and still manages to predict the clinical risk effciently and effectively. Current version of Risk-O-Meter evaluates 30-day risk of hospital readmission. However, the proposed system framework is applicable to general clinical risk predictions. In this demonstration paper, we describe different components of Risk-O-Meter and the intelligent algorithms associated with each of these components to evaluate risk of readmission using incomplete patient data inputs.
19th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), Chicago, IL
K. Zolfaghar, J. Agarwal, D. Sistla, S.-C. Chin, S. Basu Roy, and N. Verbiest
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